Rens, Gavin and Meyer, Thomas and Casini, Giovanni (2016) On Revision of Partially Specified Convex Probabilistic Belief Bases, Proceedings of 22nd European Conference on Artificial Intelligence, 29 August - 2 September, The Hague, Netherlands, 921-929, IOS Press.
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Abstract
We propose a method for an agent to revise its incomplete probabilistic beliefs when a new piece of propositional information is observed. In this work, an agent’s beliefs are represented by a set of probabilistic formulae – a belief base. The method involves de- termining a representative set of ‘boundary’ probability distributions consistent with the current belief base, revising each of these proba- bility distributions and then translating the revised information into a new belief base. We use a version of Lewis Imaging as the revision operation. The correctness of the approach is proved. An analysis of the approach is done against six rationality postulates. The expres- sivity of the belief bases under consideration are rather restricted, but has some applications. We also discuss methods of belief base revi- sion employing the notion of optimum entropy, and point out some of the benefits and difficulties in those methods. Both the boundary dis- tribution method and the optimum entropy methods are reasonable, yet yield different results.
| Item Type: | Conference paper |
|---|---|
| Uncontrolled Keywords: | Knowledge Representation Belief Revision |
| Subjects: | Computing methodologies > Artificial intelligence |
| Date Deposited: | 10 Feb 2017 |
| Last Modified: | 10 Oct 2019 15:32 |
| URI: | http://pubs.cs.uct.ac.za/id/eprint/1150 |
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